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The co-combustion of sorghum straw and paper-making sludge (PMS) is beneficial to alleviate the ash-related problem in sorghum straw combustion process. In this paper, the mineral migration and transformation behavior in sorghum straw ashes with the addition of PMS ashes under an oxidizing atmosphere were investigated using an X-ray diffractometer, thermogravimetric-derivative thermogravimetric, scanning electron microscopy-energy dispersive X-ray detector, and FactSage software. The results demonstrated that the increase in the PMS ash mass ratio led to an increase in ash fusion temperature (AFT) of sorghum straw mixtures. The generations of high melting-point (MP) calcium feldspar (e.g., Ca 2 MgSi 2 O 7 , Ca 2 Al 2 SiO 7 , Ca 3 MgSi 2 O 8 , and Ca 7 Mg (SiO 4) 4) and phosphates (e.g., Ca 3 P 2 O 8 , Ca 5 P 2 SiO 12 , and Ca 7 P 2 Si 2 O 16) caused the increases in the AFT. The maximum weight loss of sorghum straw ashes decreased with the increasing PMS ash mass ratio, and the surface of the ashes underwent the transition from smooth to a whole loose and rough, which alleviated the ash-related problems of sorghum straw. The addition of PMS ashes decreasing the liquid-phase content calculated by FactSage at the same temperature also explained the sorghum straw AFT increase. The changes of AFT and its corresponding mechanisms in the sorghum straw with PMS ash addition under an oxidizing atmosphere provided the support for large-scale combustion of biomass. • Sludge addition increased the ash fusion temperature (AFT) of sorghum straw. • Calcium containing minerals were formed due to the addition of paper-making sludge. • Ca 3 MgSi 2 O 8 , Ca 2 MgSi 2 O 7 , and Ca 2 Al 2 SiO 7 were generated caused AFT increase. • The transformation of calcium phosphates content increased with increasing temperature. • Thermogravimetric analysis of ash samples illustrated the mineral interaction. [ABSTRACT FROM AUTHOR]

Understanding the dynamics of wildfire is crucial for developing management and intervention strategies. Mathematical and computational models can be used to improve our understanding of wildfire processes and dynamics. This paper presents a systematic study of a widely used advection–diffusion–reaction wildfire model with non-linear coupling. The importance of single mechanisms is discovered by analysing hierarchical sub-models. Numerical simulations provide further insight into the dynamics. As a result, the influence of wind and model parameters such as the bulk density or the heating value on the wildfire propagation speed and the remaining biomass after the burn are assessed. Linearisation techniques for a reduced model provide surprisingly good estimates for the propagation speed in the full model. • The hierarchy of the mechanisms of an advection-diffusion-reaction wildfire model is examined analytically and numerically. • In the model, decreasing the initial biomass reduces wildfire propagation speed, with minimal effect on final biomass. • Linearisation techniques provide good approximations of the wildfire propagation speed. • The spatially lumped model provides a good prediction of the terminal biomass. [ABSTRACT FROM AUTHOR]

Rural fires are currently one of the main global disasters, and Portugal is among the countries that have suffered from them for decades. These fires pose economic, environmental, and social threats to the country. A primary cause of rural fires is the burning of biomass to clear agroforestry residues. Thus, combating rural fires requires more effective forest management, particularly the removal of forest residues that serve as fuel. These residues, also known as biomass, have significant potential for energy production and biofuel use. This paper proposes a model that integrates the PROMETHEE decision-making method with the roadmapping. This proposed model includes 7 steps, including the planning of the roadmap, the definition of the decision problem, gathering information and building the roadmap. The proposed model was applied to develop a roadmap proposal for the recovery of surplus agroforestry biomass in Portugal, identifying the most emerging conversion technologies in the national context. With the roadmap developed, it was possible to understand that the recovery of surplus agroforestry biomass in Portugal involves several sectors. The energy sector is one of those that can benefit from the recovery of leftover agroforestry biomass, both from the point of view of carbon neutrality and energy independence. Forestry management is another of the great advantages of recovering leftover forestry biomass and, consequently, reducing the number of fires. In the context of recovery, combustion is the most widely used technology for producing energy or heat. The technology identified as most emerging in the upcoming years is gasification. Investment in scientific research is essential for the success of this sector, as is the development of public incentive policies and more engagement from all stakeholders. This paper conclude that valorizing agroforestry residues can reduce rural fire risks while promoting energy independence, sustainable regional development, and innovation in Portugal. • The paper proposes an integrated PROMETHEE II-Roadmap model. • The proposed model is applied to the valorization of residual agroforestry biomass in Portugal (RAFB). • Benefits of RAFB valorization include reduction of rural fires, increased renewable energy alternatives, and sustainable regional development. • An evaluation of biomass conversion technologies is performed, and gasification is identified as the most emerging. • The paper emphasizes the need in the sector for research investment, stakeholder engagement and development of supply chains. [ABSTRACT FROM AUTHOR]

In this paper, we applied the Dispersion Normalised Positive Matrix Factorisation (DN-PMF) approach recently proposed in the literature to provide a more realistic picture of the relative importance of emission strength vs. atmospheric dispersion conditions. The disentanglement of such effects is of great concern in pollution hot spots like the Po Valley (Italy), where particulate matter limit values are exceeded despite the existing abatement measures. To explore the potentiality of the DN-PMF approach – still scarcely applied in the literature – a well-chemically characterised PM 1 (atmospheric particles with aerodynamic diameter <1 μm) dataset comprising samples collected at different time resolutions at an urban background site (Bologna) in the southern Po Valley was used. Indeed, it is well known that shallow mixing layers promote pollutant accumulation but this observation is not enough to exclude an enhancement of emission strength which could be tackled by appropriate abatement strategies. The source apportionment of sub-micron sized aerosols having a quite long atmospheric residence time in a complex environment like the Po Valley - which is also strongly impacted by secondary aerosol formation on a basin-scale - is generally quite challenging when using receptor models. Due to the availability of a huge dataset with variables having multiple time resolutions, in this work the DN-PMF was implemented in a multi-time resolution approach (MT) to achieve a better source identification and to gain knowledge about the relative importance of atmospheric dilution vs. emissions. A comparison between results obtained by the application of the regular multi time resolution (REG-MT) vs. the DN-MT approach is presented here for the five factors identified (nitrate-dominated, sulphate-dominated, biomass burning, mineral dust, and urban aerosol). The first interesting outcome is that REG-MT and DN-MT results do not point at significant differences in temporal patterns for aerosol components and sources impacting at the basin-scale (i.e. sulphate- and nitrate-dominated aerosol, biomass burning) thus suggesting that the diel modulation of these PM 1 emissions is somehow masked by the stronger variability of the mixing layer. Conversely, contributions from local sources with more pronounced diel variation like traffic are quite well reproduced by DN-MT and the ambient concentrations are enhanced compared to REG-MT. This is an important piece of information highlighting that PM 1 concentrations from local sources have been likely underestimated by REG-MT assessments. To our knowledge, this is one of the very few applications of DN-MT and the first one at a European site where the huge effort made to implement air pollution containment measures is still not very much effective in reducing PM levels; moreover, in this paper a detailed discussion about the possible interpretation of the output of DN-MT in terms of temporal patterns is reported. [Display omitted] • High PM levels are due to atmospheric stability and emission strength; DN-PMF points out the source emission role. • Secondary aerosol-dominated factors showed a regional nature. • Urban aerosol factor was highly enhanced by dispersion-normalisation. [ABSTRACT FROM AUTHOR]

Exact and trusty prediction of pollutant emissions is pivotal for optimal combustion control in biomass cogeneration systems, which possess multiple variables, high-volume data streams, and dynamic characteristics. Aiming at the multivariate dynamic systems, this paper extends a classical fast relevance vector regression (FRVR) algorithm into a multivariate form to accomplish synchronous multi-pollutant prediction. Meanwhile, a flexible and effective online training strategy is proposed to solve the problems of low accuracy of multi-step prediction and lack of dynamic updating capability. First, the given dataset is divided utilizing the k -means clustering method to enhance the clustering of similar features and expedite the prediction process. Then, the classical FRVR algorithm is extended into a multiple-output form, enabling the simultaneous prediction of multiple pollutant emissions. Moreover, the incremental learning method is introduced into the proposed multivariate FRVR model to improve its dynamic performance and online learning ability. Finally, the proposed method's effectiveness is verified through a biomass cogeneration systems case. Experimental findings fully illustrate that the proposed method provides the lower RMSE and MAE while runtime decreases by 50% and R 2 reaches 96%. The proposed method significantly outperforms others, showing excellent potential in the pollutant prediction field. • An IMFRVR algorithm is proposed to predict multiple pollutant concentrations. • The k -means method cluster the data to extract useful information from the original data. • The MFRVR model is built by setting a Gaussian distribution to the FRVR weight matrix. • The incremental learning algorithm is employed to update prediction model dynamically. [ABSTRACT FROM AUTHOR]

Frequent forest fires severely damage forest ecosystems. One potential big issue, however, is the fact that the substantial release of greenhouse gases (GHGs) from biomass combustion significantly impacts the global climate system and carbon balance. This study aims to assess the emissions of major carbon-containing gases from forest fires in mainland China between 2011 and 2021. Information on wildfires was obtained with Google Earth Engine (GEE) through the integration of MODIS products and Global Forest Above Ground Biomass (AGB) produced by the Climate Change Initiative Biomass (CCI BIOMASS) Programme. Utilizing the combustible load model and consideration of carbon emission factors in different vegetation, from 2011 to 2022, mainland China consumed an estimated 35.55 Tg C (3.23 Tg C yr−1) of above-ground combustible matter, resulting in 46.94 Tg (4.27 Tg yr−1) of carbon-containing gas emissions. Among these emissions, 42.16 Tg (3.83 Tg yr−1), 4.58 Tg (0.42 Tg yr−1), and 0.20 Tg (0.02 Tg yr−1) were attributed to CO 2 , CO, and CH 4. In general, carbon emissions from forest fires in mainland China exhibited a declining pattern with fluctuations. This indicates a substantial decrease in average annual emissions of CO 2 and CH 4 by 48.38% and 88.87%, respectively, compared to the previous century (1990s). Additionally, there was an average annual decrease in biomass consumption of approximately 35.4%. When analyzing the results on regional scales using linear regression and normalization methods, it was found that 81%–84% of provinces and regions in mainland China showed a decline in forest fire carbon emissions. Nevertheless, several areas in the northwest region displayed a noticeable rising trend. Pixel analysis is utilized in this paper to perform a spatial analysis of carbon emissions and fire locations associated with forestry fires in mainland China. This analysis clarifies the impact of combustible load distribution across different fire intensities on the interannual variability of carbon emissions from wildfires, thereby offering fire management authorities valuable insights. • Estimated carbon-containing gas emissions from wildfires in Mainland China at a pixel level in 2011–2021. • Compared 11-year average annual wildfire emissions with data from the previous century. • Explored the interrelationships among wildfire points, burnt area, net primary productivity, and fuel load. • Analyzed emission trends of major carbon gases from wildfires in Mainland China. [ABSTRACT FROM AUTHOR]

The interaction between volatile and char is widespread in combustion. The effect of this interaction on the conversion of fuel-N to NO x is significant, but the mechanism remains to be comprehensively unveiled. Thus, in this paper, the NO and N 2 O conversion of nitrogen-containing biomass models (glutamate, glycine, phenylalanine) during combustion at high temperatures (800–1500 °C) is investigated using two combustion modes, separated combustion (in which volatile and char are burned separately) and coupled combustion (in which volatile and char are burned simultaneously), in an O 2 /Ar atmosphere. A new pathway for N 2 O formation resulting from the interaction between volatile and char is identified. At low temperatures, this interaction facilitates the conversion of fuel-N to N 2 O. For instance, during the separated combustion of glutamate at 800 °C, the conversion rates of fuel-N to N 2 O and NO are 26.3 % and 20.4 %, respectively. However, in coupled combustion, these conversion rates shift to 48.1 % for N 2 O and 3.6 % for NO. At high temperatures, this interaction promotes the conversion of fuel-N to NO. For instance, during the separated combustion and coupled combustion of glutamate at 1500 °C, the conversion rates of fuel-N to NO are 6.2 % and 16.6 %, respectively. Similar patterns are observed for the other two amino acids. In both combustion modes, the co-firing of cellulose, lignin, and hemicellulose with glutamic acid significantly suppresses the production of N 2 O. The conversion rate of N 2 O decreases by about 7 %–10 %, while the impact on NO release shows either a suppressive or promotive effect in different temperature intervals. These results play a crucial role in the development of efficient and clean combustion technology for biomass. [Display omitted] • A novel N 2 O formation pathway from volatile-char interaction has been identified. • Volatile-char interaction enhances NO formation at 1300–1500 °C. • Accurate volatile-NO/N 2 O and char-NO/N 2 O contributions were determined. • Co-firing with cellulose, lignin, and hemicellulose inhibits the formation of N 2 O. [ABSTRACT FROM AUTHOR]

South Asian air pollutants exert substantial effect on the climate and environment change over the Tibetan Plateau (TP). This paper investigates the trans-boundary transport of PM 10 , PM 2.5 , and O 3 from South Asia to the TP via WRF-Chem sensitive analysis. It is found that PM 10 , PM 2.5 , and O 3 over South Asia are mainly sourced from anthropogenic sources. South Asian emissions contribute up to 54% of PM 10 (PM 2.5) in the TP in the pre-monsoon season. For O 3 , the highest contribution of 18.13% is in the monsoon season, while the lowest contribution of 8.67% is in the winter season. To evaluate the respective contributions of anthropogenic and biomass burning emissions in South Asia to PM 10 , PM 2.5 , and O 3 in the TP, anthropogenic and biomass burning emissions in South Asia are considered separately. The results show that the largest percentage contribution of PM 10 (PM 2.5) from South Asian anthropogenic emissions to PM 10 (PM 2.5) in the TP with value of 35.86% (37.77%) occurs in winter, while the lowest percentage contribution of 16.52% (16.77%) appears in the monsoon season. For O 3 , the largest contribution of 17.74% from South Asian anthropogenic emissions appears in the monsoon season, whereas the lowest contribution of 8.59% occurs in winter. Compared to the anthropogenic emissions, the biomass burning emissions in South Asia have a relative less contribution to PM 10 , PM 2.5 , and O 3 in the TP. The largest contribution of PM 10 (PM 2.5) from South Asian biomass burning emissions to PM 10 (PM 2.5) in the TP is 20.04% (18.37%) in the pre-monsoon season. Conversely, the lowest contribution of 0.58% (0.53) appears in the monsoon season. O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the TP in each season, implying that the biomass burning emissions in South Asia have little effect on O 3 in the TP. This study is of great significance to the ecological environment protection for the TP. • Contributions of South Asian emissions to PM 10 , PM 2.5 , and O 3 in the TP are quantified. • Anthropogenic emissions in South Asia have a larger contribution to PM 10 , PM 2.5 , and O 3 in the TP. • O 3 from South Asian biomass burning emissions contributes <1% to O 3 in the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

In this paper, a system for energy production from biomass combustion to provide electricity to the national grid of Vietnam was evaluated based on different thermodynamics systems and the cultivation capacity of the local area. A 20:80 mixture of cashew shell and cashew wood chip is considered as fuel source to be combusted utilizing a fixed bed technology with high energy efficiency. Considering a 10 MW production capacity to the national grid, a 20-year Net Present Value analysis and payback time evaluation was considered based on the economic factors in Vietnam. The study demonstrates how the current feed-in tariff in Vietnam is too low to encourage investment in biomass power plant. Following a suggested electricity selling price that is close to the household electric cost, the power plant shows high potential with a short payback period of 9.22 years and a levelized cost of electricity (LCOE) of only 6.4 cents/kWh. Sensitivity analyses were performed for different scenarios of material cost, electricity selling price and initial investment to show that within a 10 % variation in process factors, such project would still be able to reach payback within 20 years, with an overall LCOE of around 5–7 cents/kWh, proving the high potential of biomass-based energy production projects. • An unprecedented cashew nutshell and woodchip fuel blend is used for practicality. • On-site biomass collection and analysis were performed for accurate assessment. • FiT should be adjusted to around the household electric price to achieve payback. • An LCOE of only 6.3 cents/kWh can be attained after a 20-year lifetime. • A 10 % reduction in electricity price can increase 4 years to the payback period. [ABSTRACT FROM AUTHOR]

• A CFD biomass ignition delay model is developed. • The model is able to accurately distinguish between different biomass fuels. • The model reasonably predicts the effect of particle size on ignition. • The OH species was found to better reproduce ignition results at lower temperatures. • The CH species was found to better reproduce ignition results at higher temperatures. This paper utilizes a CFD approach to study the ignition of pulverized biomass particles. Ignition is a critical parameter in a reactor's design and process efficiency, and a reliable and relatively quick method of its determination is a necessity. CFD is a well-established tool that has already proved credible in many combustion/gasification applications, and for that reason, its application in ignition-related studies should be paramount. In this research, an Eulerian-Lagrangian approach is used where key stages during biomass combustion such as inert heating, evaporation, devolatilization, gas-phase kinetics, char conversion, particle transport, and radiative transport are considered. The predictions of the model are verified against experimentally measured ignition data from the literature and are found to be in good agreement. The ignition delay is determined by monitoring the concentrations of OH (hydroxyl) and CH (methyl) radicals. It is concluded that using OH species as ignition indicator allowed reproducing the delay better for lower temperatures, whereas, for temperatures above 1600 K, CH species was found to be more accurate. The CFD approach was eventually found reasonable and relatively fast in ignition delay predictions enabling its wider use in industrial applications. [ABSTRACT FROM AUTHOR]

While the biomass gasification and cofiring technology is promising for future energy, including green technologies, such as carbon capture and storage and bioresource feedstock, negative carbon emissions are simultaneously possible using these technologies. However, despite these functions, our previous study established that for simulating a biomass reactor, a new model needed to be designed that could improve the accuracy of both real and lab-scale simulations for carbonaceous fuels, such as coal-based applications. Hence, in this study, a biomass experiment utilizing a thermogravimetric analyzer was conducted to obtain varying reaction rate data over carbon conversion, which may then be used to simulate the biomass conversion model and 3D simulation was also conducted for a 500 MWe coal-biomass cofiring boiler. Gasification was obtained at 1000 °C and 1200 °C using CO 2 at constant temperature for different biomasses. Compared to the peak exhibited by the random pore model, biomass gasification reaction rates shifted into the later stage of the reaction, thereby yielding irregular reaction rate developments and poor prediction accuracies. With flexibility-enhanced random pore model(FERPM), we observed that correlation factors increased from the previously reported value of 0.7–0.95. In the coal-biomass cofiring boiler, the difference between the Kinetics/Diffusion-limited model and FERPM in biomass combustion aspect was examined, and it was ultimately determined that characteristics of particle reactions through FERPM are valid in 3D analysis. Therefore, this paper proposed a flexibility-enhanced random pore model proven to enhance the prediction accuracy of a simulation. • A biomass reaction development model was established and demonstrated. • The random pore model was modified to produce better prediction accuracy. • A new model was proposed based on the obtained empirical results. • The Numerical simulations of biomass gasification and combustion have been validated. [ABSTRACT FROM AUTHOR]

The production of biofuels to be used as bioenergy under combustion processes generates some gaseous emissions (CO, CO 2 , NO x , SO x , and other pollutants), affecting living organisms and requiring careful assessments. However, obtaining such information experimentally for data evaluation is costly and time-consuming and its in situ obtaining for regional biomasses (e.g. , those from Northeast Brazil (NEB) is still a major challenge. This paper reports on the application of artificial neural networks (ANNs) for the prediction of the main air pollutants (CO, CO 2 , NO, and SO 2) produced during the direct biomass combustion (N 2 /O 2 :80/20%) with the use of ultimate analysis (carbon, hydrogen, nitrogen, sulfur, and oxygen). 116 worldwide biomasses were used as input data, which is a relevant alternative to overcome the lack of experimental resources in NEB and obtain such information. Cross-validation was conducted with k-fold to optimize the ANNs and performance was analyzed with the use of statistical errors for accuracy assessments. The results showed an acceptable statistical performance for all architectures of ANNs, with 0.001–12.41% MAPE, 0.001–5.82 mg Nm−3 MAE, and 0.03–52.30 mg Nm−3 RMSE, highlighting the high precision of the emissions studied. On average, the differences between predicted and real values for CO, CO 2 , NO, and SO 2 emissions from NEB biomasses were approximately 0.01%, 10−6%, 0.14%, and 0.05%, respectively. Pearson coefficient provided consistent results of concentration of the ultimate analysis in relation to the emissions studied and effectiveness of the test set in the developed models. [Display omitted] • Assembly of a worldwide database with different lingocellulosic biomasses. • Prediction of main air pollutants (CO, CO 2 , NO, and SO 2) for the selected samples. • Information obtained on Brazilian biomasses without the need for many experiments. • Use of different evaluation metrics to validate the established models. • The ANN's showed differences between predicted and estimated values below 1.0%. [ABSTRACT FROM AUTHOR]

Summer 2019 is remembered as one of the most intense biomass burning (BB) seasons on record for the Northern Hemisphere. During the MOSAiC expedition, a smoke-dominated layer was identified in the upper troposphere over the North Pole region. The origin of this layer remains unclear, and no evidence has been found to indicate the intrusion of such particles into the Arctic Boundary Layer. The main aim of this work was to evaluate if biomass burning events in the summer 2019 were detectable at Gruvebadet Atmospheric Laboratory, close to Ny-Å lesund (Svalbard Islands) during the second half of 2019. This paper proposes an innovative approach to discriminate biomass burning events based on optical measurements combined with chemical analysis and air mass back-trajectories. Monthly background values of optical coefficients were defined using multi-annual (2018–2021) statistics and twelve possible events were identified. Source apportionment through positive matrix factorization (PMF) identified that the biomass burning factor by PMF accounted for only 2% of the total investigated concentration. The specific biomass burning tracers such as levoglucosan and phenolic compounds were compared with optical measurements and with the PMF results. Air mass trajectory analysis revealed that the early summer fires detected at Ny-Å lesund originated mainly from North America, as also confirmed by the presence of BB factor of PMF, levoglucosan and also vanillic species (softwood combustion tracers). In contrast, the chemical composition and air masses analysis of the highest peak detected in early December suggested residential heating as plausible source, further amplified by the onset of the harsh winter season and the expansion of the polar vortex towards mid-latitudes. • 12 mild pollution events have been identified investigating optical properties. • Biomass burning's contribution accounted for 2% of the total concentration. • Most of the events were detected during the fall. • The latest events in December may have been impacted by emissions from home heating. [ABSTRACT FROM AUTHOR]

The interactions among chlorine (Cl), sulfur (S), and alkaline and alkaline-earth metals (AAEMs) are the critical factors that affect the formation, transformation, and deposition of ash during biomass and coal gasification and combustion. These issues cause slagging, agglomeration, corrosion, and other problems related to the safety performance of gasifiers and boilers. A better understanding of the determination methods, modes of occurrence, migration routes, and control technologies of Cl and S is the basis for clean and efficient utilization of biomass and coal. The paper summarizes the research work in this field, namely: (1) The modes of Cl and S occurrence in biomass and coal are introduced, mainly in different forms of inorganic and organic Cl/S compounds; (2) The principles, merits and demerits of quantitative determination methods for Cl and S are sorted out and compared; (3) The migration routes of Cl and S, mainly related to their modes of occurrence, reaction evolution, temperature, and atmosphere; and (4) The interactions among Cl, S, and AAEMs and its induced issues, especially the challenging problems related to ash, including alkali-induced slagging, silicate melt-induced slagging (ash fusion), agglomeration, and corrosion. Finally, ecological and technological significance of the Cl and S release is discussed. This knowledge is of great significance to effectively control the emission of Cl and S pollutants, stable operation of gasifiers and boilers, cleaner and more efficient utilization of coal, as well as to diminish the consumption of fossil energy and heighten the availability of renewable energy in such thermochemical conversion processes. • Migration routes of chlorine and sulfur are elucidated. • Interactions among chlorine, sulfur, and AAEMs are summarized. • Ecological and technical significance of chlorine and sulfur release is discussed. [ABSTRACT FROM AUTHOR]

• Fuel quality of biomass will be improved after undergoing torrefaction pretreatment. • Correlation between torrefaction condition and biomass structural feature are summarized. • Compositional variation and elemental distribution for torrefied biomass are exemplified. • Torrefaction is beneficial to reducing the emission of gaseous pollutant and PM. Biomass is renewable and clean energy source, the utilization of biofuel derived from biomass is an important strategy to reduce CO 2 emissions and mitigate the greenhouse effect during power generation process. Biomass poses obstacles to its wide utilization in industry because of the self-characteristics such as low calorific value, high water content, poor grindability and easy corrosion decomposition. In the modern biomass conversion technologies, torrefaction pretreatment technology has attracted much attention. Torrefaction technology can generally be divided into dry torrefaction and wet torrefaction. Meanwhile, the dry torrefaction can be divided into inert torrefaction and oxidative torrefaction. From the perspective of economy and practicality, oxidative torrefaction has more prospects and advantages, such as high efficiency, low energy consumption, short pretreatment duration, et al. Based on the existing researches, a review was conducted on the field of biomass torrefaction pretreatment. Firstly, the detailed effects of torrefaction temperature, atmosphere, pressure and duration on the compositional and elemental variations of biomass were explored. Moreover, the efficiency analysis of inert torrefaction, oxidative torrefaction and flue gas torrefaction for different type biomass were also summarized and reviewed systematically. In this paper, the fuel quality and emission characteristics of torrefied biomass during thermal conversion process were also discussed respectively. Thence, the challenges and prospects of biomass torrefaction technology for the future development were also analyzed. Finally, future directions and technological challenges associated with the torrefaction process are proposed and its application potential is also evaluated. [ABSTRACT FROM AUTHOR]

Grate boilers are widely applied in biomass combustion for heat and energy generation. However, grate-firing systems often suffer from low efficiency and high emission. Computational fluid dynamic (CFD) becomes increasingly popular as a flexible method to obtain the detailed combustion behaviors in the furnace, and to optimize the performance of existing grate boilers. This paper presents efforts toward a reliable baseline CFD model for an industrial biomass-fired grate boiler, where the structure of the fuel-bed was sufficiently considered. The combustion performances in the furnace were investigated experimentally and numerically by coupling the fuel bed and freeboard, to clarify the impact of bed structure on the simulation accuracy. Results show that when the bed structure has been taken into account, the predictions are in better agreement with the various measurements, as the deviations between them are all within 10 %. Moreover, the flame center drops, the total heat transferred to the water-cooled walls increases, and the residence time of flue gas is greatly prolonged from 2.76 s to 3.90 s, resulting in a distinct difference of the temperature and species patterns in the freeboard. The simulations will provide valuable theoretical guidance for the accurate modeling of grate-fired boiler. [Display omitted] • A baseline model is proposed for accurate modeling of biomass-fired grate boiler. • Effect of fuel-bed structure on the simulation of grate boiler is clarified in detail. • Bed structure greatly affects the predicted temperature and species patterns. • Flue gas residence time and heat transfer are also highly impacted by bed structure. [ABSTRACT FROM AUTHOR]

The smooth combustion process of biomass is of great importance as the world transit away from the use of fossil fuels to embracing environmentally friendly and renewable energy. Ash-related problems, such as slagging, fouling, agglomeration, and corrosion, significantly disrupt the efficient operation of gasification systems, leading to unforeseen breakdowns. Potassium, a prevalent alkali metal in biomass, reacts with chlorine and sulfur in flue gas, generating troublesome compounds. This interaction constitutes the primary source of challenges linked to biomass combustion processes. Additives, especially kaolin, an aluminum-silicate, proved most effective in capturing potassium during combustion, forming high-melting-point potassium aluminum silicate compounds. Hence, this paper provides a summary of issues related to biomass ash, explores the deposition mechanism, outlines methods to mitigate problems associated with ash, and concludes by introducing alum sludge as an outlook. [Display omitted] • Potassium in biomass set in motion ash deposition during combustion. • Biomass ash related problem include slagging and fouling, bed agglomeration and corrosion. • The use of additives, co-combustion and leaching are biomass ash deposition remedy. • Suggestion of waste sludge as an economical alternative solution for biomass ash deposition. [ABSTRACT FROM AUTHOR]